[ Reported without editorial commentary ]

A federal jury in Oakland, California dismissed all of Elon Musk's claims against OpenAI and Sam Altman on Monday, finding that Musk waited too long to file the lawsuit. The jury deliberated for roughly 90 minutes before deciding the suit was barred by the statute of limitations. Judge Yvonne Gonzalez Rogers immediately adopted the verdict, and Musk vowed to appeal.

The ruling matters because it clears the last major legal cloud hanging over OpenAI's structure and its path to a potential IPO. OpenAI's hybrid nonprofit-and-for-profit model survives intact. The Microsoft investment in OpenAI, also challenged in the suit, was likewise dismissed. Both companies can now direct energy toward the enterprise market rather than the courtroom.

• The jury found Musk knew about OpenAI's for-profit shift as early as 2021, years before he filed suit in 2024.
• Musk had sought up to $180 billion in damages and the removal of Altman and Brockman from leadership.
• Musk's lawyer said one word to reporters leaving the courthouse: 'Appeal.'

Looking ahead, an appeal is coming, but for now OpenAI's corporate structure is legally validated and its IPO runway is clear.

--ML

Two of the biggest names in AI both decided this month that selling models is not enough. OpenAI launched the 'OpenAI Deployment Company' on May 11, a new firm designed to embed specialized engineers, called Forward Deployed Engineers, directly inside businesses to rebuild workflows around AI. It also acquired Tomoro, an applied AI firm that has already worked with companies like Tesco and Virgin Atlantic, bringing about 150 engineers on day one. Backing the new entity: TPG, Goldman Sachs, SoftBank, McKinsey, Bain, Capgemini, and a dozen other firms. Anthropic beat them to the punch in early May, forming its own enterprise services firm backed by Blackstone, Goldman Sachs, and General Atlantic, specifically aimed at community banks, mid-sized manufacturers, and regional health systems that want Claude but lack the in-house muscle to deploy it.

🧠 Ha’s Take: The biggest signal here is not that OpenAI and Anthropic launched consulting arms. It’s that even the frontier AI labs now realize AI adoption is fundamentally an organizational redesign problem, not a software deployment problem. Most companies still think they’re buying tools. What they’re actually buying is a new operating model. And the bottleneck is no longer the technology itself. It’s leadership fluency, workflow redesign, and whether organizations are willing to rethink how work happens at a foundational level. This is no longer just a Silicon Valley story. The AI transformation wave is now moving into the operational core of the broader economy.

--ML

LinkedIn laid off roughly 875 employees, about 5% of its global workforce, on May 13. The twist: revenue grew 12% year-over-year and the company crossed $5 billion in quarterly revenue for the first time. LinkedIn officially cited 'restructuring,' not AI, as the reason. But the parent company, Microsoft, is spending $190 billion on AI infrastructure in 2026, and LinkedIn's Chief Product Officer told employees internally that the goal is smaller, faster teams that 'heavily leverage AI tools.' This is the trade now: revenue goes up, headcount goes flat or down.

A new Gallup survey of 23,000 US employees found that 65% of workers at AI-adopting organizations say AI has improved their productivity, but 27% of those same workers also report high levels of disruption in the past year. BCG's research puts the challenge plainly: the real problem in the AI era is not the number of jobs affected but how quickly workers can be reskilled into redesigned roles. For CEOs, the question to answer before your next board meeting is not 'how many people will AI replace?' but 'what is our reskilling plan and when does it start?'

• More than 103,000 tech workers have lost jobs globally in 2026 so far, approaching the total for all of 2025.
• Goldman Sachs economists estimate AI is displacing roughly 16,000 US jobs per month, hitting entry-level workers hardest.

🧠 Ha’s Take: One of the hardest realities to process right now: Company growth no longer automatically means job growth. LinkedIn just crossed $5B in quarterly revenue while cutting nearly 900 jobs. And that pattern is becoming increasingly common across tech. This is bigger than “AI replacing jobs.” Companies are redesigning work around smaller, AI-augmented teams. The real challenge now is whether humans and organizations can adapt fast enough.

--ML

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